Drug Interaction Between Clopidogrel and Proton Pump Inhibitors
Bibliographic record
Abstract
Proton pump inhibitors (PPIs) have been recommended for reducing the risk of gastrointestinal bleeding associated with dual antiplatelet therapy (aspirin plus clopidogrel). However, studies have found decreased efficacy of clopidogrel when concurrently administered with a PPI. To determine the mechanism of and evidence for the potential interaction between clopidogrel and PPIs, along with the clinical implications of this drug interaction, we reviewed recently published reports of trials that examined the interaction. A MEDLINE database search (1966-September 2009) for English-language reports of clinical trials in human subjects was performed, supplemented by a manual search of reference lists. Four trials that examined surrogate outcomes and eight trials that examined clinical outcomes were included in this review. Two surrogate outcome studies showed that PPIs negatively affected clopidogrel response and increased platelet aggregation, whereas the other two did not find a significant difference between groups receiving PPIs and not receiving PPIs. Three of four published clinical outcomes studies and three of four unpublished clinical outcomes studies available as abstracts found a significant association between PPI use and rates of acute myocardial infarction, rehospitalization, death, or stroke. Most of the currently available data, primarily from observational studies, show that some PPIs may decrease clopidogrel's antiplatelet effectiveness, with increased cardiac adverse outcomes when clopidogrel is combined with PPIs. Although current data do not show causation of adverse outcomes with PPI use because the available data are conflicting, this topic is still controversial. Careful risk-benefit assessment is required before prescribing PPIs for individual patients taking dual antiplatelet therapy. More evidence from randomized controlled trials is needed to clarify this drug interaction dilemma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".